Predicting Young’s modulus of Indian coal measure rock using multiple regression and artificial neutral network

Sayantan Chakraborty, Department of Mining Engineering, Indian Institute of TechnologyKharagpur, IndiaFollow
Rohan Bisai, Department of Civil Engineering, Techno Main Salt Lake, Kolkata, India
Rohit Roy, Department of Mining Engineering, Indian Institute of TechnologyKharagpur, India
Sathish Kumar Palaniappan, Department of Mining Engineering, Indian Institute of TechnologyKharagpur, India
Samir Kumar Pal, Department of Mining Engineering, Indian Institute of TechnologyKharagpur, India
Karanam Uma Maheshwar Rao, National Institute of Technology Rourkela,India

Author ORCID Identifier

Sayantan Chakraborty: 0000-0003-2131-1249

Rohan Bisai: 0000-0001-8716-0725

Rohit Roy: 0000-0002-6567-1185

Sathish Kumar Palaniappan: 0000-0002-6799-9918

Samir Kumar Pal: 0000-0002-3140-6826

Karanam Uma Maheshwar Rao: 0000-0002-1022-5372

Abstract

Accurate information on Young’s modulus (E) is required for simulating rock deformation in mines; on the other hand, it is very cumbersome to obtain in the laboratory and collecting drilled cores in sufficient amounts, especially in the case of soft rocks, is quite impossible. Empirical equations were deducted for E from easily determinable rock properties, and the final model was selected through different statistical strength parameter tests. The generalization of the equation was verified through the normal distribution tests of residues of the equation. R2 came to be 0.609 and was validated using an artificial neural network with an improved value of 0.73

Recommended Citation

Chakraborty, Sayantan; Bisai, Rohan; Roy, Rohit; Palaniappan, Sathish Kumar; Pal, Samir Kumar; and Rao, Karanam Uma Maheshwar (2023) "Predicting Young’s modulus of Indian coal measure rock using multiple regression and artificial neutral network," Journal of Sustainable Mining: Vol. 22 : Iss. 1 , Article 4.
Available at: https://doi.org/10.46873/2300-3960.1373